Periodic Reporting for period 1 - learNoise (The neurobiological and computational origins of behavioral variability)
Reporting period: 2020-03-01 to 2022-02-28
The goal of this project was to investigate (neuro)computational mechanisms of behavioural variability, i.e. inconsistencies in our decisions, and how these inconsistencies translate into inter-individual differences in psychiatric traits, in particular impulsivity and compulsivity. Impulsivity and compulsivity are trait dimensions often linked to psychiatric disorders at their extreme ends but with substantial variability in a general population. Both dimensions have been associated with impaired cognitive flexibility, but their underlying computational implementations remained poorly understood. Understanding mechanisms underlying compulsive and impulsive behaviours pave the way for deciphering the mechanisms involved in mental health disorders such as obsessive-compulsive disorder (OCD) and attention deficit and hyperactivity disorder (ADHD). Previous research suggested that both impulsive and compulsive behaviours were driven by inconsistencies in the choice process. However, recent model advances showed that the introduction of learning imprecisions as a new source of variability substantially changes the interpretation of existing results and thus invited us to reconsider these findings. In this project, we used an innovative computational modelling approach to text how stochasticity in choice and imprecisions in learning contribute to compulsive and impulsive behaviours.
In this project through a series of large-scale online and smartphone-based experiments, we investigated how imprecisions during learning (i.e. learning noise) and stochasticity in the choice process accounted for compulsivity and impulsivity. We showed that impulsivity was tied to imprecision in learning across reward and punishment learning domains, while choice stochasticity was more linked to compulsivity. In other words, when making a decision, a compulsive individual changed their mind and explored new options, while an impulsive behaviour was rather driven by erroneous updates of the received information. These findings demonstrate that distinct neurocomputational mechanisms can drive seemingly similar behavioural deficits, only dissociable using targeted computational approaches.
In this project, we pioneered new approaches to gather large scale cognitive data. In particular, we relied on a citizen science approach, which encourages the general population to partake in research. By using gamification, we further strengthened this new methodology and pioneered it in computational psychiatry. In forthcoming articles, we further discuss the advantages and drawbacks of such approaches and their implications. We believe that such approaches will be critical for the field.
Finally, we investigated how such processes were affected by the Covid-19 pandemic. In a longitudinal study, we investigated how compulsivity was linked to Covid-19 related behaviours. We found that in contrast to depression symptoms that seem to diminish during the ease of Covid-19 restrictions, the obsessive-compulsive symptoms OC further increased and were contributing to better adherence to governmental guidelines.
Together these results advance our understanding of psychiatric traits and their behavioural and underlying computational origins. By pioneering novel approaches, our research opened up new avenues for future research.
In this project, we pioneered new approaches to gather large scale cognitive data. In particular, we relied on a citizen science approach, which encourages the general population to partake in research. By using gamification, we further strengthened this new methodology and pioneered it in computational psychiatry. In forthcoming articles, we further discuss the advantages and drawbacks of such approaches and their implications. We believe that such approaches will be critical for the field.
Finally, we investigated how such processes were affected by the Covid-19 pandemic. In a longitudinal study, we investigated how compulsivity was linked to Covid-19 related behaviours. We found that in contrast to depression symptoms that seem to diminish during the ease of Covid-19 restrictions, the obsessive-compulsive symptoms OC further increased and were contributing to better adherence to governmental guidelines.
Together these results advance our understanding of psychiatric traits and their behavioural and underlying computational origins. By pioneering novel approaches, our research opened up new avenues for future research.
In this project, we described new computational origins of impulsivity which allows us to dissociate it from compulsive behaviors. Understanding the mechanisms that drive impulsive behaviors has important implications for future research in the field of computational psychiatry, pharmacological interventions, and education.